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It is an extension of [scikit-learn](https://github.com/scikit-learn/scikit-learn).\n\n## Installation\n\n\n### Dependencies\n\n* joblib \u003e= 1.2.0\n* numpy \u003e= 1.23.3\n* pandas \u003e= 1.4.3\n* scikit_learn \u003e= 1.2.0\n* scipy \u003e= 1.10.1\n* statsmodels \u003e= 0.13.2\n* pytest = 7.2.0 (only for testing)\n\n### `pip` installation\n\nIt can be installed using *Pypi*:\n\n    pip install sslearn\n\n## Citing \n\n```bibtex\n@article{sslearn2025garrido,\n    title = {SSLearn: A Semi-Supervised Learning library for Python},\n    journal = {SoftwareX},\n    volume = {29},\n    pages = {102024},\n    year = {2025},\n    issn = {2352-7110},\n    doi = {https://doi.org/10.1016/j.softx.2024.102024},\n    author = {José L. Garrido-Labrador and Jesús M. Maudes-Raedo and Juan J. Rodríguez and César I. García-Osorio},\n}\n```\n\n## Fundings\n\nThe research carried out for the development of this software has been partially funded by the Junta de Castilla y León (project BU055P20), by the Ministry of Science and Innovation of Spain (projects PID2020-119894GB-I00 and TED 2021-129485B-C43) and by the project AIM-LAC (EP/S023992 /1). The author has been a beneficiary of the predoctoral scholarship from the Ministry of Education of the Junta de Castilla y León EDU/875/2021.\n\n\n\u003c!--Add the funding picture--\u003e\n\u003cimg width=\"100%\" src=\"https://raw.githubusercontent.com/admirable-ubu/DN-SSL/main/funding/funding_project.svg\" /\u003e\n\u003cimg width=\"100%\" src=\"https://raw.githubusercontent.com/admirable-ubu/DN-SSL/main/funding/funding_project_cyl.svg\" /\u003e\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjlgarridol%2Fsslearn","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjlgarridol%2Fsslearn","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjlgarridol%2Fsslearn/lists"}